code: def interpolate(
      input,
      size=None,
      scale_factor=None,
      mode="nearest",
      align_corners=None,
      recompute_scale_factor=None,
      antialias=False,
  ):
      if (
          mode not in ["linear", "bilinear", "bicubic", "trilinear"]
          and align_corners is not None
      ):
          raise ivy.utils.exceptions.IvyException(
              "align_corners option can only be set with the interpolating"
              f"modes: linear | bilinear | bicubic | trilinear (got {mode})"
          )
      ivy.utils.assertions.check_elem_in_list(
          ivy.get_num_dims(input),
          range(3, 6),
          message=(
              "Input Error: Only 3D, 4D and 5D input Tensors supported (got"
              f" {ivy.get_num_dims(input)}D) for the modes: nearest | linear | bilinear |"
              f" bicubic | trilinear | area | nearest-exact (got {mode})"
          ),
      )
      return ivy.interpolate(
          input,
          size,
          mode=mode,
          scale_factor=scale_factor,
          recompute_scale_factor=recompute_scale_factor,
          align_corners=bool(align_corners),
          antialias=antialias,
      )
  
file_path: ivy/ivy/functional/frontends/torch/nn/functional/vision_functions.py
imports: import ivy
  from ivy import with_unsupported_dtypes, with_supported_dtypes
  from ivy.functional.frontends.torch.func_wrapper import to_ivy_arrays_and_back
label_desc: Use image node_id 8 for calling a global function with example usage: interpolate(input, size, scale_factor, mode, align_corners, recompute_scale_factor, antialias) and returns: ivy